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Record W4406995621 · doi:10.1017/aaq.2024.65

Approaching the Past through Practice: Reconstruction of a Historical Greenlandic Dog Sled

2025· article· en· W4406995621 on OpenAlexaboutno aff
Emma Vitale

Bibliographic record

VenueAmerican Antiquity · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersAage og Johanne Louis-Hansens FondAugustinus Fonden
KeywordsHistoryGeographyArchaeologyGenealogy

Abstract

fetched live from OpenAlex

Abstract Since the emergence of the Thule culture (AD 1200), dog sledding has been perceived as a central means of transportation in traditional Inuit life in the Arctic. However, there is an absence of research concerning Inuit dog-sled technology and the tradition of the craft. This study investigates the Inuit dog-sled technocomplex using enskilment methodologiesby employing experimental and ethno-archaeological observations to explore the relationship between knowledge and technical practice. It involves the reconstruction of a historical West Greenlandic dog sled, shedding light on carpentry techniques and construction processes. This method emphasizes the interaction between humans, technology, and time, providing essential practical data for future archaeological and historical research, particularly for comprehending fragmented archaeological remains. By focusing on process rather than end product, this research provides insight into understanding Inuit dog sled technology and the complexity of the practice. The connection between artifacts and materially situated practice is demonstrated through the reconstruction of a dog sled, which illustrates the value of physicality in enskilment. It highlights how experimental archaeology can improve our insights into the historical and prehistoric Arctic societies’ technologies, economies, and practices.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.396
Teacher spread0.361 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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